Benefits of KPIs for industry sector evaluation: the case study from the Czech Republic

Loading...
Thumbnail Image
Date
Journal Title
Journal ISSN
Volume Title
Publisher
Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Abstract
Currently, there is a fourth Industrial Revolution known as Industry 4.0. This industrialization is characterized by structural changes in the substitution of labour by new technologies and capital. The paper focuses on the industrial sector, which is dominant in the Czech Republic and has a significant contribution to GDP and value added. It describes the current economic situation in Czech Republic and in European Union.
Many companies use absolute indicators (such as sales, profits, ...) or financial indicators (such as asset turnover, return on assets, ...) to evaluate their performance and efficiency. A Performance Indicator or Key Performance Indicator (KPI) is a term used by industry or professionals for assessing or type of performance measurement. The aim of the paper is to critically assess the performance evaluation of individual industries based on the absolute monitored indicators compared to the key performance indicators (KPIs). The paper contains a proposal for a KPIs system that would allow performance assessments of industry sectors, including a correlation analysis of these indicators, to allow for long-term relations. Therefore, it is possible to evaluate the performance of individual industry sectors by means of their aid.
At the same time, KPI provides sufficient information on whether to invest more in individual industrial sectors and replace human work by modern technologies or, on the contrary, whether these investments bring no added value and that it is therefore appropriate to stop them and leave this sector to other (more competitive) countries. KPI indicators gain in importance in Industry 4.0. Primary and secondary sources were used in the processing of the article.
Description
Subject(s)
industry, added value, EBIT, key performance indicators, GDP, correlation analysis
Citation
ISSN
1212-3609
ISBN
Collections